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Gee, Kevin A. – Journal of Education for Students Placed at Risk, 2018
Children from certain racial and ethnic minority backgrounds, in poverty, and/or with a disability, often face distinct challenges in attending school, leading them to miss more school relative to their non-minority, more socio-economically advantaged and non-disabled peers. This brief describes these disparities in absenteeism in the US,…
Descriptors: Attendance, Disproportionate Representation, Race, Ethnicity
Ogallo, Godfrey G. – ProQuest LLC, 2018
The rapid advancement in information technology and the ubiquitous penetration of the Internet are heralding an experience in the world where every physical device is interconnect-able to other devices and the Internet. IoT forms the core of this new wave of ubiquitous technologies. This nascent technology is opening new and virtually…
Descriptors: Data, Decision Making, Higher Education, College Students
Pritchard, Adam; McChesney, Jasper – College and University Professional Association for Human Resources, 2018
This research brief explores why "projection estimates" are not an effective approach to budget planning by comparing past projections to CUPA-HR's database of real-world salaries. The results shed light on why data-informed and data-driven decisions are a more effective way to think about budget planning. In this brief you'll learn…
Descriptors: Data Use, Budgeting, Decision Making, Higher Education
Chopra, Shivangi; Golab, Lukasz – International Educational Data Mining Society, 2018
Work-integrated learning, also known as co-operative education, allows students to alternate between on-campus classes and off-campus work terms. This provides an enhanced learning experience for students and a talent pipeline for employers. We observe that co-operative job postings are a rich source of information about the required skills,…
Descriptors: Cooperative Education, Occupational Information, Data Analysis, Job Skills
Andrews-Todd, Jessica; Forsyth, Carol; Steinberg, Jonathan; Rupp, André – International Educational Data Mining Society, 2018
In this paper, we describe a theoretically-grounded data mining approach to identify types of collaborative problem solvers based on students' interactions with an online simulation-based task about electronics concepts. In our approach, we developed an ontology to identify the theoretically-grounded features of collaborative problem solving…
Descriptors: Problem Solving, Cooperation, Student Behavior, Data Analysis
Enders, Craig K.; Hayes, Timothy; Du, Han – Grantee Submission, 2018
Literature addressing missing data handling for random coefficient models is particularly scant, and the few studies to date have focused on the fully conditional specification framework and "reverse random coefficient" imputation. Although it has not received much attention in the literature, a joint modeling strategy that uses random…
Descriptors: Data Analysis, Statistical Bias, Sample Size, Correlation
Fong, Anthony; Barrat, Vanessa; Finkelstein, Neal – WestEd, 2018
In 2015, the Governor's Office of Planning and Research commissioned an analytic study to determine the number of California students who were eligible to attend college within the University of California (UC) and/or the California State University (CSU) systems. The study, "University Eligibility Study for the Public High School Class of…
Descriptors: Eligibility, Data, Usability, High School Students
Lin, Van-Kim; King, Carlise; Maxwell, Kelly; Shaw, Sara – Administration for Children & Families, 2018
This report describes partnerships between researchers and state early childhood agencies in Georgia, Oregon, and South Carolina. Two of these partnerships are with researchers who are external to the state agency, and one is with a research team inside the agency. The report provides examples of how partnerships have made use of administrative…
Descriptors: State Agencies, Child Care, Early Childhood Education, Data Use
Hyunsuk Han – ProQuest LLC, 2018
In Huggins-Manley & Han (2017), it was shown that WLSMV global model fit indices used in structural equating modeling practice are sensitive to person parameter estimate RMSE and item difficulty parameter estimate RMSE that results from local dependence in 2-PL IRT models, particularly when conditioning on number of test items and sample size.…
Descriptors: Models, Statistical Analysis, Item Response Theory, Evaluation Methods
Peseckas, Ryan – Field Methods, 2016
I used a subscriber identity module card reader to copy the lists of saved contacts from 170 mobile phones in Fiji. This approach has both advantages and disadvantages compared to other techniques for collecting telephone network data. Copying phone contacts avoids recall biases associated with survey-based name generators. It also obviates the…
Descriptors: Handheld Devices, Social Networks, Telecommunications, Foreign Countries
Drachsler, H.; Kalz, M. – Journal of Computer Assisted Learning, 2016
The article deals with the interplay between learning analytics and massive open online courses (MOOCs) and provides a conceptual framework to situate ongoing research in the MOOC and learning analytics innovation cycle (MOLAC framework). The MOLAC framework is organized on three levels: On the micro-level, the data collection and analytics…
Descriptors: Online Courses, Data Collection, Data Analysis, Reflection
Pires, Stephen F.; Block, Steven; Belance, Ronald; Marteache, Nerea – Journal of American College Health, 2016
Objective: The present study extends research on campus smoking bans by examining where smokers are violating the policy at a large university in the southeastern region of the United States. Participants: The data collection was conducted by one graduate student from the university in August of 2014. Methods: A global positioning system device…
Descriptors: College Students, Smoking, School Policy, School Law
Willis, James E.; Slade, Sharon; Prinsloo, Paul – Educational Technology Research and Development, 2016
The growth of learning analytics as a means to improve student learning outcomes means that student data is being collected, analyzed, and applied in previously unforeseen ways. As the use of this data continues to shape academic and support interventions, there is increasing need for ethical reflection on "operational" approvals for…
Descriptors: Data Collection, Data Analysis, Educational Research, Ethics
Spector, J. Michael – Educational Technology Research and Development, 2016
This special issue of "ETR&D" is devoted to ethics in the broad domain of educational technology. Many ethical issues arise involving the study and use of educational technologies. A well-known issue involves the digital divide and the degree to which the introduction of new technologies is increasing the digital divide and…
Descriptors: Ethics, Data Collection, Data Analysis, Educational Technology
Zhao, Jensen; Zhao, Sherry Y. – Journal of Education for Business, 2016
E-business, e-education, e-government, social media, and mobile services generate and capture trillions of bytes of data every second about customers, suppliers, employees, and other types of data. The growing quantity of big data is an important part of every sector in the global economy. However, there is a significant shortage of business data…
Descriptors: Business Administration Education, Business Schools, Data Analysis, Data Processing